The data analysis Python package for the Pulsating Heat Pipe experimental data
Project description
PulseHeatPipe
PyPulseHeatPipe is a Python Library for data analysis and for data plotting/visualisation specifically for PHP experimental data.
pkg installation
pip install PyPulseHeatPipe
# for pkg upgrade
pip install --upgrade PyPulseHeatPipe
Usage:
importing the module
from PyPulseHeatPipe import PulseHeatPipe
creating the reference variable
analysis = PulseHeatPipe("datapath", "sample_name")
for a class help
help(analysis)
for a function help
help(analysis.data_etl)
using a function from the class
df, df_conv = analysis.data_etl()
to create blank file
analysis.blank_file()
list of available functions
- blank_file
- data_etl
- gibbs_fe
- data_chop
- data_stat
- data_property_avg
- best_TP
- plot_all_data
- plot_Te_Tc
- plot_eu
Example:
# importing module
from PyPulseHeatPipe import PulseHeatPipe
from PyPulseHeatPipe import DataVisualisation
analysis = PulseHeatPipe("datapaht", "sample_name")
visual = DataVisualisation("datapaht", "sample_name")
# calling help
help(analysis.data_etl)
help(visual.plot_all_data)
# using methods eg;
# for ETL
df, df_conv = analysis.data_etl()
# for visulisation of all thermal properties
visual.plot_all_data(df_gfe)
NOTE: The experimental data file must prepared in '.xlsx' format. The data must contain at least following columns with mentioned titles:
samle_data.xlsx format
t(min) | Tc[C] | Te[C] | P[bar] | Q[W] | alpha | beta | pulse |
---|---|---|---|---|---|---|---|
1 | 30 | 35 | 700 | 80 | 90 | 0 | 2 |
--- | --- | --- | --- | --- | --- | --- | --- |
here,
'time'= timestamp, 'Te[C]'= Evaporator Temperature, 'Tc[C]'= Condenser Temperature, 'P[bar]'= Pressure (gauge) of PHP, 'Q[W]'= Power Supply, 'alpha'= Horizontal Angle of PHP, 'beta'= Vertical Angle of PHP, 'pulse'= Visible pulse generation (y=1/n=0)
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